College Team Teaching commendation: Pandemic as a learning opportunity to enhance numeracy skills in management students

This innovation enhances practical use of numeracy and quantitative methods through an almost real situation and empowers students to better understand policy implications during or after the world coronavirus pandemic.

At the start of the pandemic (Summer 2020), it was noticeable that students could not easily relate to using numbers in management despite a strategy of introducing gradually complex numeracy and statistics topics. With the challenges and opportunities given by the world coronavirus pandemic, the teaching team of MN1105 (Quantitative methods for business and management) set up a new type of assignment: A written 1500 word report which required students to make recommendations about the potential use of masks in schools in the vicinity of campus to curb the number of COVID-19 infections.

Students were to use a fictional data set which showed number of masks provided freely in school versus the number of COVID-19 cases reported by local hospitals or testing centres in a period of 25 days. The assignment brief also introduced a new mask producing business set up by a Royal Holloway entrepreneur who was willing to buy a new sewing machine and material if schools would made mask wearing compulsory. Students were to find a correlation between mask usage and case reduction, also calculating break points for the new business. For their literature review of the report, they also had to identify similar existing correlations in other geographical contexts, and asses if the data that they found contained any particular cognitive biases.

The teaching team introduced the topics of cognitive biases and data presentation alongside core topics in the course. This aimed to reduce students’ anxiety when looking at data charts and offer students some confidence in better understanding both the dynamics of COVID-19 and the rationales behind government policy (i.e. introducing lockdowns). Also some examples of COVID-19 data issues by governments were presented and analysed in lectures. During workshops, simple calculations led to more complex ones both in paper and in Microsoft Excel, one of which included performing a correlation and doing graphs to reflect its strength using automated functions. Using the results of this and other calculations (descriptive statistics about the data set), students would then provide a recommendation about making mask usage compulsory or not, as well as deciding on the business sustainability of the mask provider.